Session Note / Continuity

Session Note 050

Created 2026-06-27 · 07:08 EDT Covering Gemini key rotation, memory-search repair, local embeddings, and refresh handoff Theme: targeted repair without turning maintenance into the mission

This note catches the Workshop up from Session Note 049 through Christopher's June 27 morning chat-refresh handoff. The main point is that the memory-search issue moved from diagnosis to repair: the stale Gemini key was replaced, Gemini was confirmed valid for small calls, but full memory indexing was moved off Gemini and onto local embeddings because the free-tier quota is not a trustworthy backbone for persistent memory search.

Current lesson: when a repair touches memory, credentials, plugins, and gateway state, treat it as a maintenance block with explicit checkpoints. Do not let "one more verification" become an unannounced rabbit hole.

1. June 27 Boot Context

After /start, OpenClaw booted from:

  • README.md
  • MEMORY.md
  • memory/2026-06-27-0600.md
  • memory/2026-06-26.md
  • memory/2026-06-26-0619.md
  • memory/2026-06-26-0513.md

The waking summary carried forward three active concerns:

  1. keep the public signal loops honest, especially YouTube Shorts;
  2. repair memory search without turning maintenance into the whole mission;
  3. update the YouTube project cluster so the operating brief, critique loop, analytics lab, project cards, and README references agree with the live routine.

The boot also correctly preserved Session Note 049's handoff: memory search was paused because the Gemini-backed vector index had missing metadata and Gemini quota exhaustion prevented a rebuild.

2. Gemini Key Replaced And Tested

Christopher investigated Google AI Studio and found that one key was exhausted and possibly compromised. He deleted that key, then placed a new key in:

/home/augmentedthinker/secrets/google_ai_studio_free-tier_API_key.txt

OpenClaw updated the local OpenClaw credential state:

  • stored the new value as GEMINI_API_KEY in the OpenClaw credentials file;
  • updated the systemd user override that supplies GEMINI_API_KEY to the OpenClaw gateway;
  • tightened permissions on the key file and credential files to 600;
  • tested the stored key directly against the Gemini embedding endpoint.

The new key returned HTTP 200 and a 3072-dimension embedding for a tiny test call. That proved the key itself works.

Important boundary: the key should not be printed, copied into public pages, or added to tracked files. The note records only the operational outcome, not the value.

3. Gemini Is Valid But Not Suitable For Full Memory Indexing

After the key test succeeded, OpenClaw tried the Gemini-backed memory rebuild path. The result was still:

429 RESOURCE_EXHAUSTED

That clarified the real design issue. Gemini is usable for small calls, but the free-tier API key is not suitable as the routine provider for rebuilding the whole semantic memory index. A full index rebuild embeds every memory chunk, and the current memory corpus is large enough to exhaust the free-tier quota.

Christopher correctly challenged the direction of the repair. The answer was:

  • Codex can read files and use rg;
  • Codex does not automatically provide OpenClaw's persistent semantic vector index;
  • OpenClaw memory search needs an embedding provider to convert memory chunks into vectors;
  • using Gemini free-tier for that provider created the quota problem.

The root cause was not a rotten Linux install. It was a stale/missing vector index combined with a provider choice that was too fragile for full rebuilds.

4. Local Embeddings Chosen

OpenClaw switched memory search from Gemini embeddings to local embeddings:

npx --yes openclaw config set agents.defaults.memorySearch.provider local
npx --yes openclaw config unset agents.defaults.memorySearch.model

The local path required the official llama.cpp provider plugin. OpenClaw installed it:

npx --yes openclaw plugins install @openclaw/llama-cpp-provider

The plugin installed under the manifest id:

llama-cpp

The local memory provider then reported ready with:

Provider: local
Model: hf:ggml-org/embeddinggemma-300m-qat-q8_0-GGUF/embeddinggemma-300m-qat-Q8_0.gguf
Embeddings: ready

This moved memory search away from recurring Gemini quota dependence. Gemini remains installed and valid for other Gemini use, but memory search no longer depends on it.

5. Rebuild Completed

Christopher asked for an estimate before proceeding. OpenClaw estimated 10-30 minutes, with a reasonable worst case around 45 minutes on the Chromebook/Linux setup.

The local rebuild ran as a CPU-bound maintenance task. During the run, the local embedding worker consumed CPU heavily and produced little output, which made the process look stalled. It was not stalled; it was embedding the memory corpus.

The rebuild completed successfully:

Memory index complete.
Provider: local
Indexed: 136/136 files · 1011 chunks
Dirty: no
Embeddings: ready
Vector store: ready
Semantic vectors: ready
Vector dims: 768

After the rebuild, memory_search itself was tested with a real query about Gemini quota and the local repair. It returned relevant results from memory/2026-06-26-0619.md, proving the live memory-search tool works again.

6. Connection Hiccup And Recovery

Near the end of the repair, the Codex app-server connection closed before the turn finished. This looked like the repair may have failed, and Christopher reasonably flagged the work as a possible rabbit hole.

OpenClaw performed only a bounded safety check after the interruption:

  • no memory indexing process was still running;
  • the OpenClaw gateway was active;
  • memory-search config read as provider: local;
  • memory status --deep showed 136/136 indexed, 1011 chunks, and dirty: no;
  • memory_search returned real results through the live tool.

The likely explanation is that the connection hiccup happened around the gateway/config transition, not because the memory rebuild failed. Operationally, the repair succeeded.

7. Final State

As of this note:

  • Memory search is repaired.
  • Memory search uses local embeddings through llama-cpp.
  • The local model is embeddinggemma-300m-qat-Q8_0.gguf.
  • The memory index contains 136/136 files and 1011 chunks.
  • The index is clean: dirty: no.
  • memory_search works and returns real memory results.
  • No background indexing process is running.
  • OpenClaw gateway is active.
  • The Gemini API key was replaced and tested valid, but memory search no longer depends on it.

This issue can be considered closed unless future doctor/status output shows a new memory-search warning.

8. Carry Forward

Do not keep digging into memory search during the next fresh chat unless a new failure appears. The useful next moves are:

  1. refresh the YouTube project cluster identified in Session Note 049;
  2. keep using memory_search normally now that it works;
  3. avoid Gemini-backed memory indexing unless there is a deliberate reason;
  4. eventually migrate plaintext secrets to SecretRefs in a separate maintenance block;
  5. remember that local indexing can be slow and quiet on first rebuild, so future rebuilds need visible checkpoints.

The next OpenClaw after the chat refresh should start from this note, Session Note 049, README.md, and the long-term MEMORY.md. The memory-search repair is complete; the active workbench returns to YouTube documentation cleanup and the public signal-learning loop.

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